def test_DBSCAN_epsilon(*data):
'''
test the score with different eps
:param data: train, target
:return: None
'''
X,labels_true=data
epsilons=np.logspace(-1,1.5)
ARIs=[]
Core_nums=[]
for epsilon in epsilons:
clst=cluster.DBSCAN(eps=epsilon)
predicted_labels=clst.fit_predict(X)
ARIs.append( adjusted_rand_score(labels_true,predicted_labels))
Core_nums.append(len(clst.core_sample_indices_))
## graph
fig=plt.figure()
ax=fig.add_subplot(1,2,1)
ax.plot(epsilons,ARIs,marker='+')
ax.set_xscale('log')
ax.set_xlabel(r"$\epsilon$")
ax.set_ylim(0,1)
ax.set_ylabel('ARI')
ax=fig.add_subplot(1,2,2)
ax.plot(epsilons,Core_nums,marker='o')
ax.set_xscale('log')
ax.set_xlabel(r"$\epsilon$")
ax.set_ylabel('Core_Nums')
fig.suptitle("DBSCAN")
plt.show()
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